import unicodedata
from dataclasses import dataclass
from typing import Optional, Union

import numpy as np

from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )		->	Tuple:







 '''simple docstring'''
 if isinstance(UpperCamelCase_							,					UpperCamelCase_       ):
  UpperCamelCase			  =      np.full((len(UpperCamelCase_       ), sequence_length, 2)							,					UpperCamelCase_       )
 else:
  UpperCamelCase			  =      np.full((len(UpperCamelCase_       ), sequence_length)							,					UpperCamelCase_       )

 for i, tensor in enumerate(UpperCamelCase_       ):
  if padding_side == "right":
   if isinstance(UpperCamelCase_							,					UpperCamelCase_       ):
    UpperCamelCase			  =      tensor[:sequence_length]
   else:
    UpperCamelCase			  =      tensor[:sequence_length]
  else:
   if isinstance(UpperCamelCase_							,					UpperCamelCase_       ):
    UpperCamelCase			  =      tensor[:sequence_length]
   else:
    UpperCamelCase			  =      tensor[:sequence_length]

 return out_tensor.tolist()





def 			lowercase(	UpperCamelCase_       )		->	Optional[int]:







 '''simple docstring'''
 UpperCamelCase			  =      ord(UpperCamelCase_       )
 if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126):
  return True
 UpperCamelCase			  =      unicodedata.category(UpperCamelCase_       )
 if cat.startswith("""P"""       ):
  return True
 return False


@dataclass
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase		):
   __lowerCAmelCase           =				42
   __lowerCAmelCase           =				True
   __lowerCAmelCase           =				None
   __lowerCAmelCase           =				None
   __lowerCAmelCase           =				-100
   __lowerCAmelCase           =				"pt"







   def 						lowerCamelCase_	(     self						:						List[str]   ,   lowerCamelCase_						:						Union[str, Any]				):





    """simple docstring"""


    import torch

    UpperCamelCase			  =      """label""" if """label""" in features[0].keys() else """labels"""
    UpperCamelCase			  =      [feature[label_name] for feature in features] if label_name in features[0].keys() else None
    UpperCamelCase			  =      self.tokenizer.pad(
        lowerCamelCase_   ,   padding=self.padding   ,   max_length=self.max_length   ,   pad_to_multiple_of=self.pad_to_multiple_of   ,   return_tensors="""pt""" if labels is None else None   ,   )

    if labels is None:
     return batch

    UpperCamelCase			  =      torch.tensor(batch["""entity_ids"""]				).shape[1]
    UpperCamelCase			  =      self.tokenizer.padding_side
    if padding_side == "right":
     UpperCamelCase			  =      [
         list(lowerCamelCase_				) + [self.label_pad_token_id] * (sequence_length - len(lowerCamelCase_				)) for label in labels
     ]
    else:
     UpperCamelCase			  =      [
         [self.label_pad_token_id] * (sequence_length - len(lowerCamelCase_				)) + list(lowerCamelCase_				) for label in labels
     ]

    UpperCamelCase			  =      [feature["""ner_tags"""] for feature in features]
    UpperCamelCase			  =      padding_tensor(lowerCamelCase_   ,   -1   ,   lowerCamelCase_   ,   lowerCamelCase_				)
    UpperCamelCase			  =      [feature["""original_entity_spans"""] for feature in features]
    UpperCamelCase			  =      padding_tensor(lowerCamelCase_   ,   (-1, -1)   ,   lowerCamelCase_   ,   lowerCamelCase_				)
    UpperCamelCase			  =      {k: torch.tensor(lowerCamelCase_   ,   dtype=torch.intaa				) for k, v in batch.items()}

    return batch

def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	List[str]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )
 if n == 0:
  return 0
 UpperCamelCase			  =      float("""-inf"""       )
 for i in range(1							,					n + 1       ):
  UpperCamelCase			  =      max(
      UpperCamelCase_							,					prices[i - 1] + naive_cut_rod_recursive(n - i							,					UpperCamelCase_       )       )

 return max_revue





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Optional[Any]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      [float("""-inf"""       ) for _ in range(n + 1       )]
 return _top_down_cut_rod_recursive(UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )		->	List[Any]:







 '''simple docstring'''
 if max_rev[n] >= 0:
  return max_rev[n]
 elif n == 0:
  return 0
 else:
  UpperCamelCase			  =      float("""-inf"""       )
  for i in range(1							,					n + 1       ):
   UpperCamelCase			  =      max(
       UpperCamelCase_							,					prices[i - 1] + _top_down_cut_rod_recursive(n - i							,					UpperCamelCase_							,					UpperCamelCase_       )							,					)

  UpperCamelCase			  =      max_revenue

 return max_rev[n]





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Union[str, Any]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )

 # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
 # length 0.
 UpperCamelCase			  =      [float("""-inf"""       ) for _ in range(n + 1       )]
 UpperCamelCase			  =      0

 for i in range(1							,					n + 1       ):
  UpperCamelCase			  =      max_rev[i]
  for j in range(1							,					i + 1       ):
   UpperCamelCase			  =      max(UpperCamelCase_							,					prices[j - 1] + max_rev[i - j]       )

  UpperCamelCase			  =      max_revenue_i

 return max_rev[n]





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Union[str, Any]:







 '''simple docstring'''
 if n < 0:
  UpperCamelCase			  =      f"""n must be greater than or equal to 0. Got n = {n}"""
  raise ValueError(UpperCamelCase_       )

 if n > len(UpperCamelCase_       ):
  UpperCamelCase			  =      (
      """Each integral piece of rod must have a corresponding price. """
      f"""Got n = {n} but length of prices = {len(UpperCamelCase_       )}"""
  )
  raise ValueError(UpperCamelCase_       )





def 			lowercase(	)		->	str:







 '''simple docstring'''
 UpperCamelCase			  =      [6, 10, 12, 15, 20, 23]
 UpperCamelCase			  =      len(UpperCamelCase_       )

 # the best revenue comes from cutting the rod into 6 pieces, each
 # of length 1 resulting in a revenue of 6 * 6 = 36.
 UpperCamelCase			  =      36

 UpperCamelCase			  =      top_down_cut_rod(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      bottom_up_cut_rod(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      naive_cut_rod_recursive(UpperCamelCase_							,					UpperCamelCase_       )

 assert expected_max_revenue == max_rev_top_down
 assert max_rev_top_down == max_rev_bottom_up
 assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
     main()
